JoVE | Peer Reviewed Scientific Video Journal

TOPICAL COLLECTIONS

Current Methods in Vision Research

Guest Editors

Jay Hegdé

Augusta University, Medical College of Georgia

Dr. Jay Hegdé is a computational neuroscientist who is interested in understanding how the brain works. His research focuses on understanding the brain systems for visual cognition and visually guided action, because these are excellent model systems for studying brain function at large. Dr. Hegdé is especially interested in understanding perception as inference, based on probabilistic reasoning or on heuristic judgment and decision-making (or mental ‘rules of thumb’). His doctoral work focused on the molecular biology of fruit development. He transitioned to vision research as a post-doctoral fellow. His post-doctoral work focused on a diverse array of topics in vision research, including systems neurophysiology of object perception, high-level perception of visual scenes, visual motion perception, 3D vision, visual perceptual learning, and functional organization of the visual system. This work utilized many different experimental techniques, including neurophysiological recording in awake, behaving monkeys, functional magnetic resonance imaging (fMRI) in human subjects, visual psychophysics in monkeys and humans, and neuroanatomy and cell biology of the visual system. Dr. Hegdé’s current work focuses on visual perception and visually guided action under real-world conditions, such as camouflage-breaking, invariant object recognition, and medical image perception. His laboratory also studies neural mechanisms of cross-modal (or multisensory) perception, cross-modal perceptual learning, visual impairments, and the rehabilitation visual impairments. Dr. Hegdé has enjoyed a long and productive collaboration in vision research with Dr. Bart, a co-editor of this issue. Dr. Saul, another co-editor of this issue, is a cherished fellow vision researcher of Dr. Hegdé’s at Augusta University.

Alan Saul

Augusta University, Medical College of Georgia

Dr. Alan Saul is a neurophysiologist who studies how the brain processes time. He did his undergraduate work at Caltech, working with Drs. Jack Pettigrew, Max Delbruck, Fred Thompson, and Roger Sperry. He then lived in the Central African Republic as a Peace Corps Volunteer. After teaching at an alternative high school, he got sucked back into academia and got an MS at West Virginia University, working with Dr. Paul Brown on cat dorsal horn physiology and kitten visual cortical plasticity, and with Dr. Ken Showalter on traveling waves in a chemical system. Following another year of teaching, he did PhD work at Brown University with Dr. Jerry Daniels on brief monocular experience after dark rearing in kittens. After a postdoc with Dr. Max Cynader at Dalhousie University, studying adaptation in single cells in cat visual cortex, he went to the University of Pittsburgh to work with Dr. Allen Humphrey. He showed that the lateral geniculate nucleus generates a range of response timing, providing cortex the timing used to create direction selectivity. He also demonstrated timing aftereffects in visual cortical simple cells. In Augusta, he showed that eye position could be measured precisely, recorded from lagged cells in awake monkey LGN, and demonstrated that timing is systematically altered around fixational saccades. He developed novel methods of recording electroretinograms in animals and humans. Outside of science, he works on the musical history of Eric Dolphy and Booker Little, gets around by bike, and enjoys mushrooms, hot peppers, and good beer.

Evgeniy (Eugene) Bart

Palo Alto Research Center (PARC), Palo Alto, CA

Dr. Evgeniy (Eugene) Bart is a computer scientist with an expertise in machine learning and high-level vision in humans. He is interested in understanding how learning is used to solve various visual tasks. His work focuses on high-level tasks, such as object recognition and scene interpretation. Currently, he is working on developing scene interpretation methods for document analysis. Dr. Bart obtained his doctorate from the Weizmann Institute of Science in Rehovot, Israel, under the guidance of Dr. Shimon Ullman. His doctoral work focused on how computers can use small fragments of visual images, called “extended fragments”, to recognize visual objects regardless of task-irrelevant variations, such as variations of viewpoint or illumination. His later work showed that human beings can also use such fragments to achieve invariant object recognition. His work also showed when human subjects learn to recognize novel objects, they learn such image fragments as a matter of course. Dr. Bart obtained his post-doctoral training at the Massachusetts Institute of Technology in Cambridge, MA, University of Minnesota in Minneapolis, MN, and California Institute of Technology in Pasadena, CA before assuming his current position as the Member of the Research Staff at the Palo Alto Research Center in Palo Alto, CA. In addition to his expertise in image fragments, Dr. Bart’s expertise encompasses many other broad and diverse areas in vision science, including deep learning in deep neural networks and humans, explainability, category learning in biological systems, invariant object recognition by machine and biological systems, and normalcy modeling.

Collection Overview

Vision is the mother of all senses. Primates are primarily visual animals. We use vision not just to subserve the proverbial four F’s of life, but for many higher, less mundane pursuits as well. Similarly, vision is also critical for many smart machines that operate in the real world, and for human-machine interfaces. Developing treatments and cures for visual diseases and dysfunction is an important part of biomedical research. For these reasons and more, vision research is at the forefront of scientific enquiry.

The proposed collection will cover current research methods in all aspects of vision research, broadly defined. This includes but is not limited to methods for studying visual perception and visually guided action in biological systems (molecular/cellular/developmental biology, neurophysiology, neuroimaging, psychophysics, and neuropsychology); multisensory processing, i.e., integration of visual information with other sensory information in biological systems and machines; visual impairment and dysfunction; and visual prostheses.

The overall goal of the Collection will be mainly two-fold: (1) To provide detailed and useful ‘recipes’ for various types of research for the researchers interested in incorporating these methods themselves in their own research, and (2) To provide an overview of modern vision research for more casual readers.

We welcome submissions that focus on (i) well-established methods as practiced in modern vision research, and/or (ii) newer, cutting-edge methods. Authors are welcome to contact one or more of the editors with pre-submission enquiries.